Towards a Smart, Self-scaling Cooperative Web Cache

  • Tomáš Černý
  • Petr Praus
  • Slávka Jaroměřská
  • Luboš Matl
  • Michael J. Donahoo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7147)


The traditional client/server architecture for web service delivery fails to naturally scale. This results in growing costs to the service provider for powerful hardware or extensive use of Content Distribution Networks. A P2P overlay network provides inherent scalability with multiple benefits to both clients and servers. In this paper, we provide analysis, design and prototype implementation of Cooperative Web Cache, which allows us to scale web service delivery and cope with demand spikes by employing clients in content replication. To demonstrate performance capabilities, we provide a prototype emulation for both client and server.


Overlay Network Load Time Service Result Download Time Home Node 
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  1. 1.
    Nygren, E., Sitaraman, R.K., Sun, J.: The akamai network: a platform for high-performance internet applications. SIGOPS Oper. Syst. Rev. 44, 2–19 (2010)CrossRefGoogle Scholar
  2. 2.
    Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R.H., Konwinski, A., Lee, G., Patterson, D.A., Rabkin, A., Zaharia, M.: Above the clouds: A berkeley view of cloud computing. Technical report. Berkeley (2010)Google Scholar
  3. 3.
    Stevens, W.R.: TCP/IP illustrated: the protocols, vol. 1. Addison-Wesley Longman Publishing Co., Inc., Boston (1993)zbMATHGoogle Scholar
  4. 4.
    Ullman, C., Dykes, L.: Beginning Ajax. Wrox (2007)Google Scholar
  5. 5.
    Cerny, T., Jaromerska, S., Praus, P., Matl, L., Donahoo, J.: Cooperative web cache. In: 18th International Conference on Systems, Signals and Image Processing, pp. 85–88. IEEE (2011)Google Scholar
  6. 6.
    Swen, B.: Outline of initial design of the structured hypertext transfer protocol. J. Comput. Sci. Technol. 18, 287–298 (2003)CrossRefzbMATHGoogle Scholar
  7. 7.
    Cohen, B.: Incentives Build Robustness in BitTorrent (2003)Google Scholar
  8. 8.
    Matl, L.: System for source distribution to support web application load time (cz). Master’s thesis. Czech Technical University (2011),
  9. 9.
    Rowstron, A., Druschel, P.: Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems. In: Liu, H. (ed.) Middleware 2001. LNCS, vol. 2218, pp. 329–350. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  10. 10.
    Druschel, P., Kermarrec, A.-M., Rowstron, A.: Scalable Application-Level Anycast for Highly Dynamic Groups. In: Stiller, B., Carle, G., Karsten, M., Reichl, P. (eds.) NGC 2003 and ICQT 2003. LNCS, vol. 2816, pp. 47–57. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  11. 11.
    Castro, M., Druschel, P., Kermarrec, A., Rowstron, A.: SCRIBE: A large-scale and decentralized application-level multicast infrastructure. IEEE Journal on Selected Areas in Communications 20, 1489–1499 (2002)CrossRefGoogle Scholar
  12. 12.
    Speed matters, internet speeds report (2010),
  13. 13.
    Jaromerska, S.: Environment for peer-to-peer application simulation with application on cooperative web cache. Master’s thesis. Czech Technical University (2011),
  14. 14.
    Praus, P.: Framework for network management to support simulation of varying network conditions. Master’s thesis. Czech Technical University (2011),
  15. 15.
    Wang, J.: A survey of web caching schemes for the internet. ACM SIGCOMM Computer Communication Review 29, 36–46 (1999)CrossRefGoogle Scholar
  16. 16.
    Zhu, Y.: Exploiting client caches: An approach to building large web caches. In: Proceedings of the 2003 International Conference on Parallel Processing, ICPP 2003 (2002)Google Scholar
  17. 17.
    Iyer, S., Rowstron, A., Druschel, P.: Squirrel: A decentralized peer-to-peer web cache. In: Proceedings of the Twenty-First Annual Symposium on Principles of Distributed Computing, pp. 213–222. ACM (2002)Google Scholar
  18. 18.
    Dalesa: The Peer-to-Peer Web Cache,
  19. 19.
    Linga, P., Gupta, I., Birman, K.: Kache: Peer-to-Peer Web Caching Using Kelips (2004)Google Scholar
  20. 20.
    Douceur, J.R.: The Sybil Attack. In: Druschel, P., Kaashoek, M.F., Rowstron, A. (eds.) IPTPS 2002. LNCS, vol. 2429, pp. 251–260. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  21. 21.
    Castro, M., Druschel, P., Ganesh, A., Rowstron, A., Wallach, D.: Secure routing for structured peer-to-peer overlay networks. ACM SIGOPS Operating Systems Review 36, 299–314 (2002)CrossRefGoogle Scholar
  22. 22.
    Ball, N., Pietzuch, P.: Distributed content delivery using load-aware network coordinates. In: Proceedings of the 2008 ACM CoNEXT Conference, CoNEXT 2008, pp. 77:1–77:6. ACM, New York (2008)Google Scholar
  23. 23.
    Bakiras, S., Loukopoulos, T., Papadias, D., Ahmad, I.: Adaptive schemes for distributed web caching. J. Parallel Distrib. Comput. 65, 1483–1496 (2005)CrossRefzbMATHGoogle Scholar
  24. 24.
    Spare, I.: Deploying the squid proxy server on linux. Linux J. (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Tomáš Černý
    • 1
  • Petr Praus
    • 2
  • Slávka Jaroměřská
    • 2
  • Luboš Matl
    • 1
  • Michael J. Donahoo
    • 2
  1. 1.Department of Computer Science and EngineeringCzech Technical UniversityPrague 2Czech Republic
  2. 2.Department of Computer ScienceBaylor UniversityWacoUSA

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